Though the market and excess factors can be separated by return predictors and adversarial predictors, there may still exist unrelated factors which influence the prediction performance. To further remove the interferential features and enhance the representation, we incorporate a self-distillation [1]}, [2]} method to distill the disentangled feature information from the teacher model to student model, where the teacher and student models are the same disentanglement networks in our work.
